pinkpixel-dev/apify-content-analytics
SKILLS/apify-content-analytics/SKILL.md
Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
$ install --global
skillsauthnpx skillsauth add pinkpixel-dev/skills-collection-1 apify-content-analyticsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 4, 2026, 11:17 PM22.9s2 files scanned
SKILL.md
- name:
- apify-content-analytics
- description:
- Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
- risk:
- unknown
- source:
- community
Content Analytics
Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.
Prerequisites
(No need to check it upfront)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI tool:npm install -g @apify/mcpc
Workflow
Copy this checklist and track progress:
Task Progress:
- [ ] Step 1: Identify content analytics type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analytics script
- [ ] Step 5: Summarize findings
Step 1: Identify Content Analytics Type
Select the appropriate Actor based on analytics needs:
| User Need | Actor ID | Best For |
|-----------|----------|----------|
| Post engagement metrics | apify/instagram-post-scraper | Post performance |
| Reel performance | apify/instagram-reel-scraper | Reel analytics |
| Follower growth tracking | apify/instagram-followers-count-scraper | Growth metrics |
| Comment engagement | apify/instagram-comment-scraper | Comment analysis |
| Hashtag performance | apify/instagram-hashtag-scraper | Branded hashtags |
| Mention tracking | apify/instagram-tagged-scraper | Tag tracking |
| Comprehensive metrics | apify/instagram-scraper | Full data |
| API-based analytics | apify/instagram-api-scraper | API access |
| Facebook post performance | apify/facebook-posts-scraper | Post metrics |
| Reaction analysis | apify/facebook-likes-scraper | Engagement types |
| Facebook Reels metrics | apify/facebook-reels-scraper | Reels performance |
| Ad performance tracking | apify/facebook-ads-scraper | Ad analytics |
| Facebook comment analysis | apify/facebook-comments-scraper | Comment engagement |
| Page performance audit | apify/facebook-pages-scraper | Page metrics |
| YouTube video metrics | streamers/youtube-scraper | Video performance |
| YouTube Shorts analytics | streamers/youtube-shorts-scraper | Shorts performance |
| TikTok content metrics | clockworks/tiktok-scraper | TikTok analytics |
Step 2: Fetch Actor Schema
Fetch the Actor's input schema and details dynamically using mcpc:
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"
Replace ACTOR_ID with the selected Actor (e.g., apify/instagram-post-scraper).
This returns:
- Actor description and README
- Required and optional input parameters
- Output fields (if available)
Step 3: Ask User Preferences
Before running, ask:
- Output format:
- Quick answer - Display top few results in chat (no file saved)
- CSV - Full export with all fields
- JSON - Full export in JSON format
- Number of results: Based on character of use case
Step 4: Run the Script
Quick answer (display in chat, no file):
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT'
CSV:
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.csv \
--format csv
JSON:
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.json \
--format json
Step 5: Summarize Findings
After completion, report:
- Number of content pieces analyzed
- File location and name
- Key performance insights
- Suggested next steps (deeper analysis, content optimization)
Error Handling
APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token
mcpc not found - Ask user to install npm install -g @apify/mcpc
Actor not found - Check Actor ID spelling
Run FAILED - Ask user to check Apify console link in error output
Timeout - Reduce input size or increase --timeout
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